ASSESSING THE SIMILARITIES OF 3D SIMULATION MODEL OUTCOMES
Bibliographic record
Abstract
Abstract. The recent advancement of simulation modeling to represent phenomena in three spatial dimensions (3D) requires the development of techniques that will allow comparison of the modeling outputs in multiple dimensions. However, many existing techniques for map comparison in two spatial dimensions (2D) have been developed from non-spatial method such Cohen’s Kappa. These techniques are not yet fully extended to deal with 3D map data or simulation outcomes. Therefore, the main objective of this study is to investigate the use of the 3D Accuracy and 3D Cohen’s Kappa coefficients to compare simulation model outputs in 3D. An existing agent-based model (ABM) of forest-fire smoke propagation was used to generate multiple scenarios for the purpose of comparing 3D simulation outputs. The results for 3D Accuracy and 3D Cohen’s Kappa produces meaningful values when comparing several scenarios with different 3D ABM outputs. This study emphasizes the need for the development of more advanced simulation output comparison techniques that operate in 3D and potentially over time (4D).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".